Highlights:1) Easily Train and Deploy your Spark ML and Tensorflow AI Pipelines from Local Notebooks to Production Servers7) Rapid Model A/B and Multi-armed Bandit Testing in Production with Complete Versioning and Rollback Support2) Supports Jupyter/iPython Notebook, Zeppelin, Spark, Tensorflow, HDFS, S3, Kubernetes, Docker3) Runs on all Cloud Providers including AWS, Google, Azure - as well as On-Premise4) Full GPU Support for both Training and Prediction Workloads5) Deploy Models as Optimized PMML or Generated Java and C++ Code for Native Performance on CPU/GPU6) Deploy to High Performance, Highly-Scalable, Highly-Available Netflix-based Microservices7) Full Monitoring and Metrics for All Training and Deployment Pipelines using Airflow and Prometheus8) Ingests Many Streaming Sources including Kafka, AWS Kinesis, Google Dataflow, and Apache Beam9) Built with Love and Scale by ex-Netflix, Databricks, and Tensorflow Engineers10) 24x7 Support for Everyone - All Issues Will Be Addressed!